ScopeMaster – Release History
Release 1.8.5 December x
- Added a limit to user story size
- Improvements to Spanish interpretation accuracy.
- Minor UI and security improvements
Release 1.8.2 November 26th
- NEW REST API, so you can:
- Synchronise user stories with any other tool.
- Embed user story QA as part of any CI/CD routine.
- Extract auto generated test scenarios.
- Use your existing tools to include portfolio and project reporting of functional size and user story QA.
- Check out the API documentation
- Improved Usability (several small improvements)
- Improved documentation at help.scopemaster.com
Release 1.8.1 November 3rd
- NEW Synchronise stories with Azure Devops Services (cloud)
- Improved Usability (many improvements)
- Improved security and stability
Release 1.8 October 27th
- NEW Synchronise stories with Jira Cloud and PivotalTracker
- NEW Experimental support for User Stories written in Portuguese and Spanish
- Improved stability and usability
Release 1.7.4 September 1st
- Revised algorithm allows multiple operations on the same object within a single user story
- Reference / id is used to sequence stories on the main board.
- Additional guidance on improving user stories
- Improved analyser performance
- Improved exporting (Stories, Glossary and Tests)
Release 1.7.3 August 10th
- Improved search functionality – results all sized in CFP
- Improved guidance on home screen
Release 1.7.2 July 29th
- NEW – Functional Tests Cases (downloadable)
- NEW – Glossary of definitions
- NEW – Gamificaiton – It’s fun to create great user stories and achieve 100% quality.
- Allow for Non-functional requirements, Tasks and Constraints
- Navigation improvements to make it faster and easier to improve your user stories.
- Other performance, stability and security improvements
Release 1.6.3 9th July 2019
- UX improvements
- Value Traceability – beta
Release 1.6 , 30th June 2019
- Clearer analysis presentation
- New sequence diagrams
- Option to confirm and specify users and objects.
- New, simpler, bundle-based billing
Release 1.5.2 22 June 2019
- Slice and dice your user stories like never before (by user, by object, by label). New presentation that will help you improve your user stories faster than ever.
Release 1.5.1 15 June 2019
- Upload a CSV file and map your fields dynamically – importing goes from minutes to seconds.
- Related stories – ideal for regression test targeting, a powerful cross correlation of user stories that touch the same object or user; .
- Export now includes CFP values
- Overhaul of the Labelling UX, it’s now easier than ever to label and organise your requirements, for more efficient working.
- Dozens of usability improvements – because it should be intuitive and easy to do good requirements work.
Release 1.4.5 24 May 2019
- User story title is no longer analysed for data movement intent
- Other usability, cosmetic and stability improvements
Pre-Production release 0.88, 25 March 2018
- Improved full screen display and responsive menus
- Improved defects report
- Easy navigation back to recently visited user stories
Pre-Production release 0.87, 17 March 2018
- NEW Sortable, searchable table, ideal for story grooming
- Improved text analysis accuracy
- Simplified defects report
- Improved performance for very large projects
Pre-Production release 0.85, 6 March 2018
- NEW Users can share work with others in their organization.
- NEW Share work at the application level: owners can assign read or edit access to others in their organisation.
- NEW Requirement text within square brackets will be ignored from sizing analysis.
- NEW Requirement export/download as csv.
- Improved IFPUG Function Point estimates, with function-by-function details report.
- Improved text analysis accuracy.
- Improved UI and bug fixes.
- Improved searching
- Improved application performance.
- Improvements to application data security.
- Major improvements to server(s) security.
Beta, 14 December 2017
- analyses the text to describe software requirements
- Interprets user story terminology and common active phrases
- identifies candidate users and objects from the entire body of requirements text
- detects potentially defective requirements – ambiguous
- detects potentially defective requirements – omissions
- detects potentially defective requirements – duplicates
- Identifies functional data movements
- Identifies data to be maintained
- estimates the functional size of the software – in Cosmic Function Points
- provides estimates for: cost to develop, defect potentials, resource requirements and likely schedules.
- Accuracy of functional sizing is currently around 70-80% (Nb. manual accuracy can vary by up to 10%)
- Import by text list or csv
- Ability to take a snapshot track the size progression.
- Portfolio view
- Import 2 column spreadsheet
- Basic text analysis engine
- Initial CFP structure